Ant colony optimization for continuous domains

The ant colony algorithm has been successfully used to solve discrete problems. However, its discrete nature restricts applications to the continuous domains. In this paper, we introduce two methods of ACO for solving continuous domains. The first method references the thought of ACO in discrete space and need to divide continuous space into several regions and the pheromone is assigned on each region discrete, the ants depend on the pheromone to construct the path and find the solution finally. Compared with the first method, the second one which the distribution of pheromone in definition domain is simulated with normal distribution has essential difference to the first one. In order to improve the solving ability of those two algorithms, the pattern search method will be used. Experimental results on a set of test functions show that those two algorithms can obtain the solution in continuous domains well.